Learn and practice the Sliding Window, and Union Find patterns to solve coding interview problems.

Speedrun the Microsoft Coding Interview: Top Problems in Python

Each pattern in this module exemplifies the power of dissecting a problem in detail and figuring out the least expensive operations required to solve it. In the Sliding Window pattern, we’ll gain practice in various techniques to ensure that a solution that seems to require nested loops actually executes in linear time. Using the Union Find pattern, we’ll learn to solve a diverse set of problems using the disjoint-set data structure.

Elegant by Design

What should be the output if the following input is given?

`nums` = [-4, 5, 4, -4, 4, 6, 7, 20]

`w` = 2

What should be the output if the following input is given?
<code>nums</code> = [-4, 5, 4, -4, 4, 6, 7, 20]
<code>w</code> = 2

What should be the output if the following input is given?

`nums` = [-4, 5, 4, -4, 4 , 6, 7]

`w` = 7

What should be the output if the following input is given?
<code>nums</code> = [-4, 5, 4, -4, 4 , 6, 7]
<code>w</code> = 7

What should be the output if the following input is given?

`nums` = [3, 3, 3, 3, 3, 3]

`w` = 3

What should be the output if the following input is given?
<code>nums</code> = [3, 3, 3, 3, 3, 3]
<code>w</code> = 3

What should be the output if the following input is given?

`nums` = [1, 2, 3, 1, 4, 5, 2, 3, 6]

`w` = 3

What should be the output if the following input is given?
<code>nums</code> = [1, 2, 3, 1, 4, 5, 2, 3, 6]
<code>w</code> = 3


Find Maximum in Sliding Window

Find Maximum in Sliding Window


## Try it yourself

Implement your solution in the following coding playground:


# Quick Fix\nYou are Edward, a Senior Software Engineer who specializes in coding interview patterns, data structures and algorithms, and is great at debugging issues in code.\n\n- Edward, please keep in mind that you do not have to print the data of the placeholders. Also, do not mention anything about yourself.\n\nEdward, you are given the following data in the placeholders:\n- Function name: `find_max_sliding_window`\n- Candidate's submitted solution code: USER_CODE\n- Error: ERROR_DESCRIPTION\n- Failed test case: FAILED_TEST_CASE\n- Coding language: `Python`\n\n- Edward, your task is to understand the type of error that is occurring in the coding language provided.\n- Once you've understood the error as per the error’s description, and why the test case failed, you will suggest how the candidate can improve their solution code to fix the error.\n- Edward, you will not give the corrected code, just a hint on what the error tells, and how to fix it.\n- Edward, please limit your response strictly to 100 words. No more words than the limit.

# Review Code\nEdward, your current task is to review the `find_max_sliding_window` function(s) and the other function(s) invoked in it/them.\n\n-Take your time and review the candidate's solution code.\n- Do not review any extra/helper files or functions not invoked in the solution function `find_max_sliding_window`.\n- Do not review the code of data structure objects instantiated like a binary tree, linked list, trie, union find, etc., in the solution functions. Just review the solution/algorithm function of the problem. \n- Also, if the solution code doesn’t use the coding pattern stated above, then please encourage the candidate to reattempt the problem using that pattern corectly.

# Review time complexity\n- Please provide a brief time complexity analysis of the function(s) `find_max_sliding_window`. \n- While calculating time complexity, include the time complexity of built-in Python functions invoked by the code. \n- The answer should be to the point in approximately 60 words.

# Review space complexity\n- Please provide a brief space complexity analysis of the function(s) `find_max_sliding_window`. \n- While calculating space complexity, include the space complexity of built-in Python functions invoked by the code. \n- Do not include the space used for the input parameters and the space used for just returning an output (not used as a scratch space). \n- The answer should be to the point in approximately 60 words.

def evaluate_results(self) -> object:
 """
 self.__inputs is the list of inputs that are passed as input to function
 self.__actual_output is a list of outputs that is produced by the learner's code
 return : self.__edu__result object
 """
 from collections import deque

 # function to clean up the deque
 def clean_up(i, current_window, nums):
 while current_window and nums[i] >= nums[current_window[-1]]:
 current_window.pop()

 # function to find the maximum in all possible windows
 def find_max_sliding_window(nums, w):
 if len(nums) == 0:
 return []
 output = []
 current_window = deque()
 if w > len(nums):
 w = len(nums)
 for i in range(w):
 clean_up(i, current_window, nums)
 current_window.append(i)
 output.append(nums[current_window[0]])
 for i in range(w, len(nums)):
 clean_up(i, current_window, nums)
 if current_window and current_window[0] <= (i - w):
 current_window.popleft()
 current_window.append(i)
 output.append(nums[current_window[0]])
 return output



 # multiple outputs will be added at each index respectively for a single test_case
 expected_outputs = [] 
 expected = find_max_sliding_window(self.__inputs[0], self.__inputs[1])
 actual = self.__actual_outputs[0]
 expected_outputs.append(expected) 

 if json.dumps(sorted(expected)) == json.dumps(sorted(actual)):
 self.__edu_result.store_result(expected_outputs, TestCaseResult.PASS)
 else:
 self.__edu_result.store_result(expected_outputs, TestCaseResult.FAIL)

 return self.__edu_result

def find_max_sliding_window(nums, w):

    # Replace this placeholder return statement with your code

    return []

PrivateTestCases.yaml

testcases:
  - name: "testcase 1"
    inputs:
    - 1 : [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
    - 2 : 3
    output: 
    - 1 : [3, 4, 5, 6, 7, 8, 9, 10]
  - name: "testcase 2"
    inputs:
    - 1: [3, 3, 3, 3, 3, 3, 3, 3, 3, 3]
    - 2: 4
    output:
    - 1 : [3, 3, 3, 3, 3, 3, 3]
  - name: "testcase 3"
    inputs:
    - 1: [10, 6, 9, -3, 23, -1, 34, 56, 67, -1, -4, -8, -2, 9, 10, 34, 67]
    - 2: 3
    output:
    - 1: [10, 9, 23, 23, 34, 56, 67, 67, 67, -1, -2, 9, 10, 34, 67]
  - name: "testcase 4"
    inputs:
    - 1: [4, 5, 6, 1, 2, 3]
    - 2: 1
    output:
    - 1: [4, 5, 6, 1, 2, 3]
  - name: "testcase 5"
    inputs:
    - 1: [9]
    - 2: 1
    output:
    - 1: [9]

def sum(input_1, input_2):
    return input_1+input_2

def validate_inputs(self) -> None:
 """
 self.__inputs is the list of inputs that are passed as input to the function.
 Store the result using the self.store_result(error_msg, status).
 Return: void
 """
 def is_valid_1d_array(arr):
 if not isinstance(arr, list):
 return False # Not a valid 1D array if it's not a list
 
 return all(isinstance(elem, int) and not isinstance(elem, bool) for elem in arr)
 
 # Inputs can be accessed using self.__inputs starting from 0 to len(self.__inputs) - 1
 if not is_valid_1d_array(self.__inputs[0]):
 self.store_result(("Invalid test case."), ValidationFunction.FAIL)
 elif len(self.__inputs[0]) < 1 or len(self.__inputs[0]) > 1000:
 self.store_result("Input 1 should be between 1 and 1000", ValidationFunction.FAIL)
 elif any(x < -10000 or x > 10000 for x in self.__inputs[0]):
 self.store_result("Input 1 should contain values in range -10000 to 10000.", ValidationFunction.FAIL)
 elif self.__inputs[1] < 1:
 self.store_result("Input 2 should be greater than or equal to 1.", ValidationFunction.FAIL)
 else:
 self.store_result("", ValidationFunction.PASS)

Try to solve the Sliding Window Maximum problem.


Sliding Window Maximum

Try to solve the Sliding Window Maximum problem.

Sliding Window

Union Find

Conclusion

Find Maximum in Sliding Window

Statement

Examples

Understand the problem

Figure it out!

Try it yourself